HONOR PTP-N49
Geekbench AI Score
1254
Single Precision Score
1233
Half Precision Score
2070
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | y561994 |
| Upload Date | November 28 2025 05:20 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm SM8750 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | HONOR PTP-N49 |
| Model ID | HONOR PTP-N49 |
| Motherboard | PTP |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm SM8750 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.32 GHz |
| Memory Information | |
|---|---|
| Size | 10.94 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
994
184.8 IPS |
|
|
Image Classification (HP)
|
100% |
837
155.6 IPS |
|
|
Image Classification (Q)
|
100% |
1819
338.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1024
16.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
1066
17.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
2207
35.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
2530
2.95 IPS |
|
|
Pose Estimation (HP)
|
100% |
2480
2.89 IPS |
|
|
Pose Estimation (Q)
|
84% |
6208
7.36 IPS |
|
|
Object Detection (SP)
|
98% |
813
64.7 IPS |
|
|
Object Detection (HP)
|
98% |
762
60.6 IPS |
|
|
Object Detection (Q)
|
83% |
1434
115.9 IPS |
|
|
Face Detection (SP)
|
100% |
2000
23.8 IPS |
|
|
Face Detection (HP)
|
100% |
2155
25.6 IPS |
|
|
Face Detection (Q)
|
95% |
3800
45.4 IPS |
|
|
Depth Estimation (SP)
|
99% |
1918
14.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
1930
14.9 IPS |
|
|
Depth Estimation (Q)
|
64% |
3806
34.9 IPS |
|
|
Style Transfer (SP)
|
89% |
5042
6.54 IPS |
|
|
Style Transfer (HP)
|
89% |
5145
6.68 IPS |
|
|
Style Transfer (Q)
|
98% |
9521
12.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1016
37.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1070
39.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2316
85.8 IPS |
|
|
Text Classification (SP)
|
100% |
366
488.8 IPS |
|
|
Text Classification (HP)
|
99% |
337
450.3 IPS |
|
|
Text Classification (Q)
|
88% |
412
555.6 IPS |
|
|
Machine Translation (SP)
|
100% |
642
11.1 IPS |
|
|
Machine Translation (HP)
|
100% |
626
10.8 IPS |
|
|
Machine Translation (Q)
|
50% |
309
11.0 IPS |
